2023 EACL EACL 2023

A Crosslinguistic Database for Combinatorial and Semantic Properties of Attitude Predicates

Abstract

AbstractWe introduce a cross-linguistic database for attitude predicates, which references their combinatorial (syntactic) and semantic properties. Our data allows assessment of cross-linguistic generalizations about attitude predicates as well as discovery of new typological/cross-linguistic patterns. This paper motivates empirical and theoretical issues that our database will help to address, the sample predicates and the properties that it references, as well as our design and methodological choices. Two case studies illustrate how the database can be used to assess validity of cross-linguistic generalizations.

🧭 Keyword Pioneer — typological pattern
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Robotics, Speech & Audio